ALBERT

Description: Folding one-dimensional polymer chains into well-defined topologies represents an important organization process for proteins, but replicating this process for supramolecular polymers remains a challenging task. We report supramolecular polymers that can fold into protein-like topologies. Our approach is based on curvature-forming supramolecular rosettes, which affords kinetic control over the extent of helical folding in the resulting supramolecular fibers by changing the cooling rate for polymerization. When using a slow cooling rate, we obtained misfolded fibers containing a minor amount of helical domains that folded on a time scale of days into unique topologies reminiscent of the protein tertiary structures. Thermodynamic analysis of fibers with varying degrees of folding revealed that the folding is accompanied by a large enthalpic gain. The self-folding proceeds via ordering of misfolded domains in the main chain using helical domains as templates, as fully misfolded fibers prepared by a fast cooling rate do not self-fold.

Description: The excitonic insulator is an intriguing electronic phase of condensed excitons. A prominent candidate is the small bandgap semiconductor Ta 2 NiSe 5 , in which excitons are believed to undergo a Bose-Einstein condensation–like transition. However, direct experimental evidence for the existence of a coherent condensate in this material is still missing. A direct fingerprint of such a state would be the observation of its collective modes, which are equivalent to the Higgs and Goldstone modes in superconductors. We report evidence for the existence of a coherent amplitude response in the excitonic insulator phase of Ta 2 NiSe 5 . Using nonlinear excitations with short laser pulses, we identify a phonon-coupled state of the condensate that can be understood as a novel amplitude mode. The condensate density contribution substantiates the picture of an electronically driven phase transition and characterizes the transient order parameter of the excitonic insulator as a function of temperature and excitation density.

Description: We present the application of a global carbon cycle modeling system to the estimation of monthly regional CO2 fluxes from the column-averaged mole fractions of CO2 (XCO2) retrieved from spectral observations made by the Greenhouse gases Observing SATellite (GOSAT). The regional flux estimates are to be publicly disseminated as the GOSAT Level 4 data product. The forward modeling components of the system include an atmospheric tracer transport model, an anthropogenic emissions inventory, a terrestrial biosphere exchange model, and an oceanic flux model. The atmospheric tracer transport was simulated using isentropic coordinates in the stratosphere and was tuned to reproduce the age of air. We used a fossil fuel emission inventory based on large point source data and observations of nighttime lights. The terrestrial biospheric model was optimized by fitting model parameters to observed atmospheric CO2 seasonal cycle, net primary production data, and a biomass distribution map. The oceanic surface pCO2 distribution was estimated with a 4-D variational data assimilation system based on reanalyzed ocean currents. Monthly CO2 fluxes of 64 sub-continental regions, between June 2009 and May 2010, were estimated from GOSAT FTS SWIR Level 2 XCO2 retrievals (ver. 02.00) gridded to 5° × 5° cells and averaged on a monthly basis and monthly-mean GLOBALVIEW-CO2 data. Our result indicated that adding the GOSAT XCO2 retrievals to the GLOBALVIEW data in the flux estimation brings changes to fluxes of tropics and other remote regions where the surface-based data are sparse. The uncertainties of these remote fluxes were reduced by as much as 60% through such addition. Optimized fluxes estimated for many of these regions, were brought closer to the prior fluxes by the addition of the GOSAT retrievals. In most of the regions and seasons considered here, the estimated fluxes fell within the range of natural flux variabilities estimated with the component models.

Description: We present the application of an integrated global carbon cycle modeling system to the estimation of monthly regional CO2 fluxes from the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from the spectral observations made by the Greenhouse gases Observing SATellite (GOSAT). The regional flux estimates are to be publicly disseminated as the GOSAT Level 4 data product. The forward modeling components of the system include an atmospheric tracer transport model, an anthropogenic emissions inventory, a terrestrial biosphere exchange model, and an oceanic flux model. The atmospheric tracer transport was simulated using isentropic coordinates in the stratosphere and was tuned to reproduce the age of air. We used a fossil fuel emission inventory based on large point source data and observations of nighttime lights. The terrestrial biospheric model was optimized by fitting model parameters to match observed atmospheric CO2 seasonal cycle, net primary production data, and a biomass distribution map. The oceanic surface pCO2 distribution was estimated with a 4-D variational data assimilation system based on reanalyzed ocean currents. Monthly CO2 fluxes of 64 sub-continental regions, between June 2009 and May 2010, were estimated from the GOSAT FTS SWIR Level 2 XCO2 retrievals (ver. 02.00) gridded to 5° × 5° cells and averaged on a monthly basis and monthly-mean GLOBALVIEW-CO2 surface-based observations. Our result indicated that adding the GOSAT XCO2 retrievals to the GLOBALVIEW observations in the flux estimation would bring changes to fluxes of tropics and other remote regions where the surface-based observations are sparse. The uncertainty of these remote fluxes was reduced by as much as 60% through such addition. For many of these regions, optimized fluxes are brought closer to the prior fluxes by the addition of GOSAT data. For the most of the regions and seasons considered here, the estimated fluxes fell within the range of natural flux variability estimated with the component models.

Description: Even though the maximum wind radius (Rmax) is an important parameter in determining the intensity and size of tropical cyclones, it has been overlooked in previous storm surge studies. This research reviewed the existing estimation methods of Rmax based on the central pressure or maximum wind speed. These over or underestimated Rmax because of the substantial variety of the data, though an average radius could be moderately estimated. Alternatively, we proposed an Rmax estimation method based on the radius of the 50 knot wind (R50). The data obtained during the passage of strong typhoons by a meteorological station network in the Japanese archipelago enabled us to derive the following formula, Rmax = 0.23R50. Although this new method substantially improved the estimation of Rmax compared to the existing models, an estimation error was unavoidable because of fundamental uncertainties regarding the typhoon's structure or insufficient number of available typhoon data. In fact, a numerical simulation from 2013 Typhoon Haiyan demonstrated a substantial difference in the storm surge height for different Rmax. Therefore, the variability of Rmax should be taken into account in storm surge simulations, independently of the model used, to minimize the risk of over or underestimation of storm surges. The proposed method is expected to increase the reliability of storm surge prediction and contribute to disaster risk management, particularly in the Western North Pacific, including countries such as Japan, China, Taiwan, Philippines, and Vietnam.

Description: We present a study on validation of the National Institute for Environmental Studies Transport Model (NIES TM) by comparing to observed vertical profiles of atmospheric CO2. The model uses a hybrid sigma-isentropic (σ–θ) vertical coordinate that employs both terrain-following and isentropic parts switched smoothly in the stratosphere. The model transport is driven by reanalyzed meteorological fields and designed to simulate seasonal and diurnal cycles, synoptic variations, and spatial distributions of atmospheric chemical constituents in the troposphere. The model simulations were run for biosphere, fossil fuel, air–ocean exchange, biomass burning and inverse correction fluxes of carbon dioxide (CO2) by GOSAT Level 4 product. We compared the NIES TM simulated fluxes with data from the HIAPER Pole-to-Pole Observations (HIPPO) Merged 10 s Meteorology, Atmospheric Chemistry, and Aerosol Data, including HIPPO-1, HIPPO-2 and HIPPO-3 from 128.0° E to −84.0° W, and 87.0° N to −67.2° S. The simulation results were compared with CO2 observations made in January and November 2009, and March and April 2010. The analysis attests that the model is good enough to simulate vertical profiles with errors generally within 1–2 ppmv, except for the lower stratosphere in the Northern Hemisphere high latitudes.